code: def test_min_max_norm(self):
      constraint_fn = constraints.MinMaxNorm(
          min_value=0.2, max_value=0.5
      )
      output = constraint_fn(get_example_array())
      output = backend.convert_to_numpy(output)
      l2 = np.sqrt(np.sum(np.square(output), axis=0))
      self.assertFalse(l2[l2 < 0.2])
      self.assertFalse(l2[l2 > 0.5 + 1e-6])
  
file_path: keras/keras/constraints/constraints_test.py
imports: import numpy
  from keras import backend
  from keras import constraints
  from keras import testing
label_desc: Use image node_id 4 for calling the ConstraintsTest obj's underlying member method code with example usage: obj.test_min_max_norm() without return types